Node Placement Research Articles

Enhancing Smart Building Surveillance Systems in Thin Walls: An Efficient Barrier Design.

This paper introduces an efficient barrier model for enhancing smart building surveillance in harsh environment with thin walls and structures. After the main research problem of minimizing the total number of wall-recognition surveillance barriers, we propose two distinct algorithms, Centralized Node Deployment and Adaptation Node Deployment, which are designed to address the challenge by strategic placement of surveillance nodes within the smart building. The Centralized Node Deployment aligns nodes along the thin walls, ensuring consistent communication coverage and effectively countering potential disruptions. Conversely, the Adaptation Node Deployment begins with random node placement, which adapts over time to ensure efficient communication across the building. The novelty of this work is in designing a novel barrier system to achieve energy efficiency and reinforced surveillance in a thin-wall environment. Instead of a real environment, we use an ad hoc server for simulations with various scenarios and parameters. Then, two different algorithms are executed through those simulation environments and settings. Also, with detailed discussions, we provide the performance analysis, which shows that both algorithms deliver similar performance metrics over extended periods, indicating their suitability for long-term operation in smart infrastructure.

Delay and Energy Efficient Offloading Strategies for an IoT Integrated Water Distribution System in Smart Cities

In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate challenges in the distribution network networks such as leakage, breakage, theft, overflow, dry running of pumps and so on. However, the increase in the number of communication and sensing devices within smart cities has evoked challenges to existing communication networks due to the increase in delay and energy consumption within the network. The work presents different strategies for efficient delay and energy offloading in IoT-integrated water distribution systems in smart cities. Different IoT-enabled communication network topology diagrams are proposed, considering the different water network design parameters, land cover patterns and wireless channels for communication. From these topologies and by considering all the relevant communication parameters, the optimum communication network architecture to continuously monitor a water distribution network in a metropolitan city in India is identified. As a case study, an IoT design and analysis model is studied for a secondary metropolitan city in India. The selected study area is in Kochi, India. Based on the site-specific model and land use and land cover pattern, delay and energy modeling of the IoT-based water distribution system is discussed. Algorithms for node categorisation and edge-to-fog allocation are discussed, and numerical analyses of delay and energy models are included. An approximation of the delay and energy of the network is calculated using these models. On the basis of these study results, and state transition diagrams, the optimum placement of fog nodes linked with edge nodes and a cloud server could be carried out. Also, by considering different scenarios, up to a 40% improvement in energy efficiency can be achieved by incorporating a greater number of states in the state transition diagram. These strategies could be utilized in implementing delay and energy-efficient IoT-enabled communication networks for site-specific applications.

Cross-domain interactions confer stability to benthic biofilms in proglacial streams

Cross-domain interactions are an integral part of the success of biofilms in natural environments but remain poorly understood. Here, we describe cross-domain interactions in stream biofilms draining proglacial floodplains in the Swiss Alps. These streams, as a consequence of the retreat of glaciers, are characterised by multiple environmental gradients and perturbations (e.g., changes in channel geomorphology, discharge) that depend on the time since deglaciation. We evaluate co-occurrence of bacteria and eukaryotic communities along streams and show that key community members have disproportionate effects on the stability of community networks. The topology of the networks, here quantified as the arrangement of the constituent nodes formed by specific taxa, was independent of stream type and their apparent environmental stability. However, network stability against fragmentation was higher in the streams draining proglacial terrain that was more recently deglaciated. We find that bacteria, eukaryotic photoautotrophs, and fungi are central to the stability of these networks, which fragment upon the removal of both pro- and eukaryotic taxa. Key taxa are not always abundant, suggesting an underlying functional component to their contributions. Thus, we show that there is a key role played by individual taxa in determining microbial community stability of glacier-fed streams.

Optimal relay nodes placement with game theory optimization for Wireless Sensor Networks

Wireless Sensor Networks (WSN) play a major role in the wide variety of applications like underground pipeline and leaks monitoring, temperature distribution monitoring in industrial cyber systems, military, forest life monitoring, and environmental and geographical monitoring. Sensors are widely used in these different applications. The number of sensors and the application concerned mainly decides the energy consumption, network lifetime. In this process relay nodes may help the sensors as backbone to connect with sink node or base stations. In this paper, we introduce a new approach for relay node selection in WSN to minimize the energy consumption of the network. It uses channel aware relay selection technique using game theory optimization and act as a virtual backbone in connecting to the base station. However, the relay nodes are varied to check the optimal number of relays required for the small, medium and large number of nodes deployed in the network. Simulations are carried out using Network Simulator NS-2.35 and network is analyzed in wide variety of scenarios. Results show that the proposed relay node selection algorithm reduces energy consumption, improves lifetime, throughput of the network.

Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric Visualizations.

Visualizing relational data is crucial for understanding complex connections between entities in social networks, political affiliations, or biological interactions. Well-known representations like node-link diagrams and adjacency matrices offer valuable insights, but their effectiveness relies on the ability to identify patterns in the underlying topological structure. Reordering strategies and layout algorithms play a vital role in the visualization process since the arrangement of nodes, edges, or cells influences the visibility of these patterns. The BioFabric visualization combines elements of node-link diagrams and adjacency matrices, leveraging the strengths of both, the visual clarity of node-link diagrams and the tabular organization of adjacency matrices. A unique characteristic of BioFabric is the possibility to reorder nodes and edges separately. This raises the question of which combination of layout algorithms best reveals certain patterns. In this paper, we discuss patterns and anti-patterns in BioFabric, such as staircases or escalators, relate them to already established patterns, and propose metrics to evaluate their quality. Based on these quality metrics, we compared combinations of well-established reordering techniques applied to BioFabric with a well-known benchmark data set. Our experiments indicate that the edge order has a stronger influence on revealing patterns than the node layout. The results show that the best combination for revealing staircases is a barycentric node layout, together with an edge order based on node indices and length. Our research contributes a first building block for many promising future research directions, which we also share and discuss. A free copy of this paper and all supplemental materials are available at https://osf.io/9mt8r/?view_only = b70dfbe550e3404f83059afdc60184c6.

Energy-Efficient Relay Node Placement in Wireless Heterogeneous Networks with Capacity Constraints

In wireless heterogeneous networks (HetNets), rational relay node (RN) placement can not only expand network coverage and capacity, but also significantly reduce energy consumption of the network. However, existing RN placement schemes mainly focus on improving network performance, and do not take the network energy consumption and capacity constraints of RNs into consideration, which makes their solutions impractical. Therefore, in this paper, we investigate energy-efficient RN placement (EERPL) problem, and try to reduce energy consumption of a wireless HetNet within the range of RN’s capacity constraints. More specifically, we first present a fine-grained energy consumption model and formulate the EERPL problem, which can be translated to the degree constrained minimum Steiner tree problem. Then, we propose a heuristic RN-placement algorithm HBAPS, which involves two steps, i.e., generating an initial minimum-energy RN placement solution and adjusting the solution to be with in the capacity constraints. Finally, extensive simulations are conducted in both randomly generated scenarios and real trace-based scenarios. Experimental results demonstrate that HBAPS achieves nearly optimal results when the scenario is small, and even in a large scenario, the proposed algorithm still obtains proper solutions within the acceptable time, and outperforms the other two existing heuristic algorithms.

Critical Analysis of Hominidae (Great Ape) Taxonomy

This article is a critical look at the current taxonomic placement of the different species that make up Hominidae (the great ape family) to determine if any biases might be occurring in how humans are described relative to the other great apes and how taxonomic placements are understood across different disciplines. A systematic literature review was conducted to quantify the placement of the human node on the phylogenetic trees that were observed. The qualitative data includes a literature review of the philosophical/religious and linguistic perspectives and noting when the colloquial and scientific terms were used and in what context. Three taxonomic placements were presented in this thesis: the currently accepted Hominidae family, 2) the separated Hominidae-Pongidea families, and 3) an updated taxonomic placement that result from the findings in this research. The data from the quantitative and qualitative analyses were observed and the use of language were used to determine that there is a bias when researchers illustrate the taxonomic relationship of humans and other great apes. The main findings were humans, chimpanzees, bonobos, and gorillas all belong to genus Homo, and failure to group all these organisms in a single genus produces a bias within the research and leads to paraphyletic groupings where humans are perceived as separate from other great apes. This bias reinforces institutional pithecophobia in Western society that perpetuate the belief that humans are separate from other apes.

A Review Study of the Optimized Cluster Head Placement of Transmit-Only Nodes in Wireless Sensor Networks

Wireless sensor networks (WSNs) with transmit-only (TO) nodes are gaining increased popularity, in particular, in applications requiring heavy deployment of sensor nodes in harsh and inaccessible environments. The data collected by the members of the WSN is relayed to a nearby base station (BS) via a cluster-head (CH). Since the nodes are usually battery-limited, it is important to optimize the location of the CH in the sensing environment to prolong the lifetime of the entire network. In this paper, we describe this problem using a general energy model and review the main articles that discuss the energy optimization problem in WSNs and summarize their important results, in addition to the basic working principles of the different widely used energy-optimization algorithms.

Automatic Generation of Topology Diagrams for Strongly-Meshed Power Transmission Systems

Topology diagrams are widely seen in power system applications, but their automatic generation is often easier said than done. When facing power transmission systems with strongly-meshed structures, existing approaches can hardly produce topology diagrams catering to the aesthetics of readers. This paper proposes an integrated framework for generating aesthetically-pleasing topology diagrams for power transmission systems. Input with a rough layout, the framework first conducts visibility region analysis to reduce line crossings and then solves a mixed-integer linear programming problem to optimize the arrangement of nodes. Given that the complexity of both modules is pretty high, simplification heuristics are also proposed to enhance the efficiency of the framework. Case studies on several power transmission systems containing up to 2,046 nodes demonstrate the capability of the proposed framework in generating topology diagrams conforming to aesthetic criteria in the power system community. Compared with the widespread force-directed algorithm, the proposed framework can preserve the relative positions of nodes in the original layout to a great extent, which significantly contributes to the identification of electrical elements on the diagrams. Meanwhile, the time consumption is acceptable for practical applications.

Traffic-Aware Trusted Node Placement and Resource Allocation in Multi-Band EONs Secured with QKD

Traffic-Aware Trusted Node Placement and Resource Allocation in Multi-Band EONs Secured with QKD

DAAG-SNP: Energy Efficient Distance and Angulation-Based Agglomerative Clustering for Sink Node Placement

DAAG-SNP: Energy Efficient Distance and Angulation-Based Agglomerative Clustering for Sink Node Placement

WG-SLSQP: Weighted Geometric Based Sequential Least Square Programming for Sink Node Placement in WBAN

WG-SLSQP: Weighted Geometric Based Sequential Least Square Programming for Sink Node Placement in WBAN

Energy Efficient Optimal User Association and Node Placement Mechanism for Cooperative UAV Communications

Energy Efficient Optimal User Association and Node Placement Mechanism for Cooperative UAV Communications

Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis

Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis

Evaluating the Potential of Mesh Networks in Enhancing Rural Connectivity based on Internet of Thing

Rural communities struggle to connect to the internet, a phenomenon known as the digital divide. Mesh networks, with improved access in rural regions, might help to tackle this problem. From a social, economic, and scientific standpoint, this study investigated whether mesh networks may improve rural connectivity. This project developed and implemented methodologies to assess community participation, cost, and network coverage. Five well-known methods were pitted against these ones. Locals are working on a mesh node placement project in a rural location with diverse topography. In terms of network coverage, the Network Coverage Assessment revealed that the proposed approach frequently outperformed the most recent approaches. Finding the ideal locations for mesh nodes helped to tackle challenges in rural regions. After putting the strategy into effect, the Cost-Effectiveness Analysis revealed a positive ROI. Many alternative options seemed unprofitable. On the Community Engagement Index, the recommended method performed better than others. Participating in network activities with individuals from the local community helps to foster ownership and shared accountability.

Wireless Sensor Networks for Precision Agriculture: A Review of NPK Sensor Implementations.

The integration of Wireless Sensor Networks (WSNs) into agricultural areas has had a significant impact and has provided new, more complex, efficient, and structured solutions for enhancing crop production. This study reviews the role of Wireless Sensor Networks (WSNs) in monitoring the macronutrient content of plants. This review study focuses on identifying the types of sensors used to measure macronutrients, determining sensor placement within agricultural areas, implementing wireless technology for sensor communication, and selecting device transmission intervals and ratings. The study of NPK (nitrogen, phosphorus, potassium) monitoring using sensor technology in precision agriculture is of high significance in efforts to improve agricultural productivity and efficiency. Incorporating Wireless Sensor Networks (WSNs) into the ongoing progress of proposed sensor node placement design has been a significant facet of this study. Meanwhile, the assessment based on soil samples analyzed for macronutrient content, conducted directly in relation to the comparison between the NPK sensors deployed in this research and the laboratory control sensors, reveals an error rate of 8.47% and can be deemed as a relatively satisfactory outcome. In addition to fostering technological innovations and precision farming solutions, in future this research aims to increase agricultural yields, particularly by enabling the cultivation of certain crops in locations different from their original ones.

Linear/Non-Linear Energy Harvesting Models via Multi-Antenna Relay Cooperation in V2V Communications

Vehicle-to-vehicle (V2V) communications is a part of next-generation wireless networks to create smart cities with the connectivity of intelligent transportation systems. Besides, green communications is considered in V2V communication systems for energy sustainability and carbon neutrality. In this scope, radio-frequency (RF) energy harvesting (EH) provides a battery-free energy source as a solution for the future of V2V communications. Herein, the employment of RF-EH in V2V communications is considered where the bit error probability (BEP) of a dual-hop decode-and-forward relaying system is obtained depending on the utilization of antennas at the relay. The multiple antenna power-constraint relay harvests its power by applying dedicated antenna (DA)/power splitting (PS) EH modes and linear (L)/nonlinear (NL) EH models. Moreover, the links between nodes are exposed to double-Rayleigh fading. Finally, the performance of different system parameters is compared using theoretical derivations of BEP. The results provide a comprehensive analysis of the proposed system considering PS/DA-EH modes and L/NL-EH models, as well as deterministic/uniformly distributed placement of nodes. It is observed that PS-EH outperforms DA-EH assuming a placement of an equal number of antennas and distances. Moreover, optimal performance of PS/DA-EH is achieved by allocating more power and increasing the number of antennas for EH, respectively.

An efficient 3-approximation algorithm for the Steiner tree problem with the minimum number of Steiner points and bounded edge length.

We present improved algorithms for the Steiner tree problem with the minimum number of Steiner points and bounded edge length. Given n terminal points in a 2D Euclidean plane and an edge length bound, the problem asks to construct a spanning tree of n terminal points with minimal Steiner points such that every edge length of the spanning tree is within the given bound. This problem is known to be NP-hard and has practical applications such as relay node placements in wireless networks, wavelength-division multiplexing(WDM) optimal network design, and VLSI design. The best-known deterministic approximation algorithm has O(n3) running time with an approximation ratio of 3. This paper proposes an efficient approximation algorithm using the Voronoi diagram that guarantees an approximation ratio of 3 in O(n log n) time. We also present the first exact algorithm to find an optimal Steiner tree for given three terminal points in constant time. Using this exact algorithm, we improve the 3-approximation algorithm with better performance regarding the number of required Steiner points in O(n log n) time.

Adaptive squirrel coyote optimization-based secured energy efficient routing technique for large scale WSN with multiple sink nodes

In general, Wireless Sensor Networks (WSNs) require secure routing approaches for delivering the data packets to their sinks or destinations. Most of the WSNs identify particular events in their explicit platforms. However, several WSNs may examine multiple events using numerous sensors in a similar place. Multi-sink and multi-hop WSNs include the ability to offer network efficiency by securing effective data exchanges. The group of nodes in the multi-sink scenario is described through a distance vector. Though, the efficiency of multi-sink WSNs is considerably impacted by the routing of data packets and sink node placement in the cluster. In addition, many WSNs for diverse reasons existed in the similar geographical region. Hence, in this task, a secured energy-efficient routing technique is designed for a Wireless sensor network with Large-scale and multiple sink nodes. Here, the concept of an improved meta-heuristic algorithm termed Adaptive Squirrel Coyote Search Optimization (ASCSO) is implemented for selecting the accurate selection of cluster head. The fitness function regarding residual distance, security risk, energy, delay, trust, and Quality of Service (QoS) is used for rating the optimal solutions. The consumption of energy can be reduced by measuring the mean length along with the cluster head and multiple sink nodes. The latest two heuristic algorithms such as Coyote Optimization Algorithm (COA) and Squirrel Search Algorithm (SSA) are integrated for suggesting a new hybrid heuristic technique. Finally, the offered work is validated and evaluated by comparing it with several optimization algorithms regarding different evaluation metrics between the sensor and sink node.

Guaranteeing Zero Secrecy Outage in Relaying Systems under Eavesdropper’s Arbitrary Location and Unlimited Number of Antennas

This paper proposes a three-phase transmission scheme to ensure zero secrecy outage in decode-and-forward relay systems by using the strategies of artificial noise (AN) injection and channel state information (CSI) leakage avoidance. The zero-outage secrecy spectral efficiency (ZOSSE) and energy efficiency (ZOSEE) of the scheme are then analyzed. Finally, the paper demonstrates that the scheme can always achieve zero secrecy outage even when the eavesdropper has an unlimited number of antennas or is in an arbitrary location, which shows its practical applicability. The paper also shows that the ZOSSE increases with the transmit power and that both the ZOSSE and the ZOSEE are maximized when the relay is halfway between the transmitter and the receiver. This suggests that the placement of the helper node is important in securing the communication of two distant nodes.